This book argues for an innovative approach to the systematic learning of metaphorical expressions, idioms and proverbs.Based on conceptual metaphor and image schema theory,a 4-level hierarchical framework is established,which originates from embodied experiences,and surfaces in linguistic expressions including metaphorical expressions,idioms,and proverbs.Because conceptual metaphors,image,and image schemas posess special cognitive features,it is claimed that they can facilitate the learning of linguistic expressions organized or motivated by them.Supports are identified from the following sources of evidence: The Dual Coding Theory,the Psychological Reality of Image Schema,and the Psychological Reality of Hierarchical Structure.The effectiveness of the current approach is experimentally explored and examined by means of five studies with the participation of four hundred plus Chinese undergraduate students.The present research represents an attempt to bridge the gap between the theoretical study of conceptual metaphors and image schemas in cognitive linguistics and their pedagogical applications in applied linguistics.
A companion to the Insight Toolkit An introduction to the theory of modern medical image processing, including the analysis of data from - X-ray computer tomography, - magnetic resonance imaging, - nuclear medicine, - and ultrasound. Using an algorithmic approach, and providing the mathematical, statistical, or signal processing as needed for background, the authors describe the principles of all methods implemented in the Insight Toolkit (ITK), a freely available, open- source, object-oriented library. The emphasis is on providing intuitive descriptions of the principles and illustrative examples of results from the leading filtering, segmentation, and registration methods. This book covers the mathematical foundations of important techniques such as: - Statistical pattern recognition, - PDE-based nonlinear image filtering, - Markov random fields, - Level set methods, - Deformable models, - Mutual information, image-based registration - Non-rigid image data fusion With contributions from: Elsa Angelini, Brian Avants, Stephen Aylward, Ting Chen, Jeffrey Duda, Jim Gee, Luis Ibanez, Celina Imielinska, Yinpeng Jin, Jisung Kim, Bill Lorensen, Dimitris Metaxas, Lydia Ng, Punam Saha, George Stetten, Tessa Sundaram, Jay Udupa, Ross Whitaker, Terry Yoo, and Ying Zhuge. The Insight Toolkit is part of the Visible Human Project from the National Library of Medicine, with support from NIDCR, NINDS, NIMH, NEI, NSF, TATRC, NCI, and NIDCD.
Now available in a new hardback edition, Michael Camille´s Image on the Edge explores that riotous realm of marginal art, so often explained away as mere decoration or zany doodles, where resistance to social constraints flourished.
Modern life is a sea of images. With so much visual data bombarding us-from personal devices to mass media-our brains must rapidly adapt to make sense of it all. Here to guide us is America´s premier intellectual provocateur, Camille Paglia. In these pages, Paglia returns to the subject that made her famous, situating our current visual environment within the epic scope of all of art history. With trademark audacity, Paglia tours through more than two dozen seminal paintings, sculptures, architectural styles, performance pieces, and digital art works that have transformed our world. Combining close analysis with historical context, she trains our eye to each image-from an Egyptian tomb to Jackson Pollock´s abstract Green Silver to Renée Cox´s daring performance piece Chillin´ with Liberty. And in her stunning conclusion, she declares the avant-garde tradition dead and film director George Lucas the world´s greatest living artist. Written with energy, erudition, and wit, Glittering Images will profoundly change the way we see.
This book introduces the classical and modern image reconstruction technologies. It covers topics in two-dimensional (2D) parallel-beam and fan-beam imaging, three-dimensional (3D) parallel ray, parallel plane, and cone-beam imaging. Both analytical and iterative methods are presented. The applications in X-ray CT, SPECT (single photon emission computed tomography), PET (positron emission tomography), and MRI (magnetic resonance imaging) are discussed. Contemporary research results in exact region-of-interest (ROI) reconstruction with truncated projections, Katsevich´s cone-beam filtered backprojection algorithm, and reconstruction with highly under-sampled data are included. The last chapter of the book is devoted to the techniques of using a fast analytical algorithm to reconstruct an image that is equivalent to an iterative reconstruction. These techniques are the author´s most recent research results. This book is intended for students, engineers, and researchers who are interested in medical image reconstruction. Written in a non-mathematical way, this book provides an easy access to modern mathematical methods in medical imaging. Table of Content:Chapter 1 Basic Principles of Tomography1.1 Tomography1.2 Projection1.3 Image Reconstruction1.4 Backprojection1.5 Mathematical ExpressionsProblemsReferencesChapter 2 Parallel-Beam Image Reconstruction2.1 Fourier Transform2.2 Central Slice Theorem2.3 Reconstruction Algorithms2.4 A Computer Simulation2.5 ROI Reconstruction with Truncated Projections2.6 Mathematical Expressions (The Fourier Transform and Convolution , The Hilbert Transform and the Finite Hilbert Transform , Proof of the Central Slice Theorem, Derivation of the Filtered Backprojection Algorithm , Expression of the Convolution Backprojection Algorithm, Expression of the Radon Inversion Formula ,Derivation of the Backprojection-then-Filtering AlgorithmProblemsReferencesChapter 3 Fan-Beam Image Reconstruction3.1 Fan-Beam Geometry and Point Spread Function3.2 Parallel-Beam to Fan-Beam Algorithm Conversion3.3 Short Scan3.4 Mathematical Expressions (Derivation of a Filtered Backprojection Fan-Beam Algorithm, A Fan-Beam Algorithm Using the Derivative and the Hilbert Transform)ProblemsReferencesChapter 4 Transmission and Emission Tomography4.1 X-Ray Computed Tomography4.2 Positron Emission Tomography and Single Photon Emission Computed Tomography4.3 Attenuation Correction for Emission Tomography4.4 Mathematical ExpressionsProblemsReferencesChapter 5 3D Image Reconstruction5.1 Parallel Line-Integral Data5.2 Parallel Plane-Integral Data5.3 Cone-Beam Data (Feldkamp´s Algorithm, Grangeat´s Algorithm, Katsevich´s Algorithm)5.4 Mathematical Expressions (Backprojection-then-Filtering for Parallel Line-Integral Data, Filtered Backprojection Algorithm for Parallel Line-Integral Data, 3D Radon Inversion Formula, 3D Backprojection-then-Filtering Algorithm for Radon Data, Feldkamp´s Algorithm, Tuy´s Relationship, Grangeat´s Relationship, Katsevich´s Algorithm)ProblemsReferencesChapter 6 Iterative Reconstruction6.1 Solving a System of Linear Equations6.2 Algebraic Reconstruction Technique6.3 Gradient Descent Algorithms6.4 Maximum-Likelihood Expectation-Maximization Algorithms6.5 Ordered-Subset Expectation-Maximization Algorithm6.6 Noise Handling (Analytical Methods, Iterative Methods, Iterative Methods)6.7 Noise Modeling as a Likelihood Function6.8 Including Prior Knowledge6.9 Mathematical Expressions (ART, Conjugate Gradient Algorithm, ML-EM, OS-EM, Green´s One-Step Late Algorithm, Matched and Unmatched Projector/Backprojector Pairs )6.10 Reconstruction Using Highly Undersampled Data with l0 MinimizationProblemsReferencesChapter 7 MRI Reconstruction7.1 The ´M´7.2 The ´R´7.3 The ´I´; (To Obtain z-Information, x-Information, y-Information)7.4 Mathematical ExpressionsProblemsReferencesIndexing